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1. An Experian Perspective
The Power of Data Integrity and Quality

2. Talking about data quality eventually means
talking about data governance. In most data-driven
organizations, the mindset is to have technology
teams run and manage all data assets. IT managers,
when given the task of improving data, often look
at practical breakdowns or system incidents to help
direct their focus. In short, they make improvements
based on their known faults.
A recent study by Forrester Research indicates that
fewer than 15 percent of data-driven organizations
have business-led data governance and quality
disciplines.1
As such, organizations are failing
to align their core business objectives with their
operating models. Companies that have relied
heavily on IT managers to direct quality standards
now are realizing that data management needs
to be owned and sponsored by the business
and must become more formal.
This shift from IT to business-led means
that organizations will need the appropriate
business tools to help support this new era
of data management and oversight. With the
right tools, business owners will have the ability
to size, sample and test data across a variety
of performance metrics and set the appropriate
guidelines for improvements.
Business leaders ultimately will create data
improvements that align with regulatory
mandates, consumer expectations and core
business strategies.
15%Less
than
of data driven
organizations
have business led
data governance &
quality disciplines
— Forrester Research
Mastering Data Quality —
Are You Ready
for Governance?
1
Fewer
than
of data-driven
organizations have
business-led data
governance and
quality disciplines.
1
Information Management, Forrester Research. Are Data Governance Tools Ready
for Data Governance? June 26,2014. http://www.information-management.com/blogs/

3. Data Credibility
Beyond data quality metrics, is your data credible? This is the
next line of questioning that may come your way from regulators
and other external parties that are focused and chartered to test
and sample your data.
In this data-driven age, and with the focus on data accuracy and
completeness, the question of credibility may prove to be a hot topic.
Regulators no longer are accepting small subset data samples, or
proxy samples, to satisfy their data assessments; they are looking
for larger data sets from the originating data systems (or systems
of record) in order to perform their assessments. Their view may
be to take the largest possible data samples in order to assert the
credibility and viability of complex data systems and platforms.
Organizations with sloppy data management practices may be
viewed as not having credible data. Knowing that your systems are
doing what they are supposed to do and generating the correct data
on a byte-by-byte basis is crucial to establishing quality data and
asserting data credibility.
The question of
credibility
may prove to be a
hot
topic.
2
View on-demand webinar
and learn how to implement
focused data integrity strategies.

4. The Investment in Quality Assurance
The life cycle of consumer credit data begins and ends with the lender. After it leaves your organization, the data
appears on a variety of materials, including the customer statement, marketing solicitations, the credit report and
future product offers.
Consumer information is a key component for risk models and in determining what type of products your company
might offer to a particular customer. The data influences future decisions related to credit offers, including rates and
terms specifically for products such as personal lines of credit, auto loans and mortgages.
As a result, it is critical to capture accurate consumer information at the onset of the initial purchase, as well as to
implement processes that continually evaluate the validity of the data. Applying such methods will help reduce the
risk of your organization receiving incomplete or imprecise data throughout the life cycle. The investment you make
in quality assurance will maximize targeting and marketing efforts, ensure effective cross-sell and drive a higher
return of quality consumer data.
3
Data
Management
System
Inaccurate data
Accurate data
Poor decision,
missed opportunity
Good decision,
profitable outcome

5. January 2012:
The CFPB launches its
nonbank supervisory role
(e.g., payday lenders).
December 2013:
The CFPB expands its
supervisory role of nonbank
student loan services.
December 2013:
The CFPB orders a direct
bank to pay $80 million
for discriminatory
auto loan pricing.
January 2014:
Supervisory exams begin
on larger collection
companies. Their
findings include failure
to investigate disputes.
January 2014:
The CFPB begins
action against
mortgage kickbacks.
June 2014:
The CFPB launches
an inquiry into
mobile banking.
April 2014:
The SECURE Act is proposed to set
requirements for credit reporting
agencies, lenders and data providers
to maintain accurate data.
November 2013:
The CFPB puts debt collectors on
notice regarding fair practices.
December 2013:
The CFPB orders a
mortgage company
to refund $125 million.
Enforcement and Accountability
The Consumer Financial Protection Bureau (CFPB) continues to work hard at asserting its mission of protecting
consumers from financial harm. As such, the CFPB has delivered numerous commentaries regarding the disciplines
of data management and overall improvements needed in order to reflect accurate customer data.
The focus of the CFPB remains clear: to enforce the rules that have long been established to protect the rights
of consumers and to hold accountable those entities that knowingly and unknowingly violate those rights.
To date, the CFPB has been expanding its supervisory role over various industries. The CFPB’s review and
examination processes thus far have resulted in a variety of fines, assessments and penalties to those entities
that have not done well in meeting their stated obligations to the consumer.
In short, all types of lending companies are being scrutinized — mortgage firms, debt collectors, payday lenders,
consumer finance and auto lenders, to name a few. As noted in American Banker,2
“the CFPB has already begun
looking into college partnerships with financial institutions. It has also issued a rule to supervise the largest student
loan service providers.”
4
2
American Banker, Capitol Hill Takes Hard Look at Student Lending, June 4, 2014
http://www.americanbanker.com/issues/179_107/capitol-hill-takes-hard-look-at-student-lending-1067892-1.html

6. The financial services industry as a whole continues to face mounting pressures to meet the highest standards
of data reporting and accuracy. While new regulations and mandates continue to impact the way companies do
business, the consumer remains at the center of it all.
Externally, companies are faced with regulatory audits and exams. Investors and market analysts continue to demand
high returns on investments and assurances of ongoing growth and success. Internally, business leaders are looking
to strategize business opportunities and to improve cost efficiencies and minimize operational and credit risks.
Despite all these competing activities, the focus needs to remain on the customer. Customer loyalty and retention
and positive customer experiences, remain critical components to a company’s future. Economic challenges and
strict lending practices have cultivated a more educated, empowered and financially aware consumer. As a result,
consumers want more insight into their credit data and on how they can improve creditworthiness, further increasing
the demand for accurate credit reports.
Cultivating the appropriate data management practices is essential to ensuring a positive customer experience.
Credit data accurately reflected on a loan statement and on a consumer’s credit report helps to create a respected
relationship between the consumer and the credit provider.
The Lens Is Wide, Sharp and Focused
Despite all these
competing activities,
the focus
needs to
remain on
the customer.
5

7. Are You Prepared?
How Do You Achieve Data Quality?
DO YOU...
(e.g., payday
lenders)
Nov 2013:
CFPB puts debt
collectors on
notice re: fair
practices
student loan
services
Dec 2013:
CFPB orders
mortgage
company to
refund $125MM
discriminatory
auto loan pricing
Jan 2014:
CFPB begins
action against
mortgage
kickbacks
Findings: failure to
investigate disputes
Apr 2014:
SECURE Act proposed that would
set requirements for credit bureaus,
lenders, and data providers to
maintain accurate data
mobile
banking
Be proactive and
prepared when
addressing regulators
Address consumer
concerns
Achieve
operational
efficiencies
Ensure data
accuracy
Promoteapositive
customer experience
Take corrective
actions to improve
Review data governance?
Correct errors in data submissions?
Complete an audit of data submissions?
Evaluate disputes and resolutions?
Compare data to peers and the industry?
Review existing policies and processes?
YES
Achieving data quality is an ongoing investment
for any organization. The key ingredients for
successful data quality programs include:
• Data Governance
• Well-defined Sampling
and Testing Methods
• State-of-the-art Tools
• Ability to Perform Analyses
• Comparative Metrics
• Strong Data Partners
• Key Leadership Endorsement
• Sponsorship
6

8. Contributing authors:
Ashley Chin, Carmen Hearn
1 888 414 1120
www.experian.com
At Experian, we are committed to helping our current and future clients achieve data quality. To deliver on
our promise, we offer products, services and an experienced team dedicated to receiving and maintaining
a repository of data that accurately reflects consumer credit information.
Experian Data Integrity Services
SM
can help data furnishers gain insight into their Metro 2®
data submissions,
identify and correct rejected accounts, and understand dispute statistics. Additionally, a data quality review
with peer benchmarking information can be delivered in a dashboard tool that allows clients to interact with
and filter reported data. Experian Data Integrity Services
SM
may include internal or external consultant support.
Our Global Consulting Practice offers a comprehensive custom review of data governance, policy and process
documentation and provides implementation recommendations and support.
Be proactive and prepared with Experian Data Integrity Services.
SM
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